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Record W3129989946 · doi:10.1155/2021/6674144

Relationship of Stress Test Findings to Anatomic or Functional Extent of Coronary Artery Disease Assessed by Coronary Computed Tomography Angiography‐Derived Fractional Flow Reserve

2021· article· en· W3129989946 on OpenAlexaff
Demetrios Doukas, Sorcha Allen, Amy Wozniak, Siri Kunchakarra, Rina Verma, Jessica Marot, John J. López, Koen Nieman, Gianluca Pontone, Jonathon Leipsic, Jeroen J. Bax, Mark Rabbat

Bibliographic record

VenueBioMed Research International · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersNational Heart, Lung, and Blood InstituteLoyola Medicine
KeywordsMedicineFractional flow reserveCoronary artery diseaseChest painCardiologyInternal medicineStenosisComputed tomography angiographyStress testing (software)RadiologyCoronary arteriesStress EchocardiographyCoronary angiographyAngiographyArteryMyocardial infarction

Abstract

fetched live from OpenAlex

Background. In the United States, functional stress testing is the primary imaging modality for patients with stable symptoms suspected to represent coronary artery disease (CAD). Coronary computed tomography angiography (CTA) is excellent at identifying anatomic coronary artery disease (CAD). The application of computational fluid dynamics to coronary CTA allows fractional flow reserve (FFR) to be calculated noninvasively (FFRCT). The relationship of noninvasive stress testing to coronary CTA and FFRCT in real‐world clinical practice has not been studied. Methods. We evaluated 206 consecutive patients at Loyola University Chicago with suspected CAD who underwent noninvasive stress testing followed by coronary CTA and FFRCT when indicated. Patients were categorized by stress test results (positive, negative, indeterminate, and equivocal). Duke treadmill score (DTS), METS, exercise duration, and chest pain with exercise were analyzed. Lesions ≥ 50%stenosis were considered positive by coronary CTA. FFRCT < 0.80 was considered diagnostic of ischemia. Results. Two hundred and six patients had paired noninvasive stress test and coronary CTA/FFRCT results. The median time from stress test to coronary CTA was 49 days. Average patient age was 60.3 years, and 42% were male. Of the 206 stress tests, 75% were exercise (70% echocardiographic, 26% nuclear, and 4% EKG). There were no associations of stress test results with CAD > 50% or FFRCT < 0.80 (p = 0.927 and p = 0.910, respectively). Of those with a positive stress test, only 30% (3/10) had CAD > 50% and only 50% (5/10) had FFRCT < 0.80. Chest pain with exercise did not correlate with CAD > 50% or FFRCT < 0.80 (p = 0.66 and p = 0.12, respectively). There were no significant correlations between METS, DTS, or exercise duration and FFRCT (r = 0.093, p = 0.274; r = 0.012, p = 0.883; and r = 0.034, p = 0.680; respectively). Conclusion. Noninvasive stress testing, functional capacity, chest pain with exercise, and DTS are not associated with anatomic or functional CAD using a diagnostic strategy of coronary CTA and FFRCT.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.356
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2021
Admission routes1
Has abstractyes

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